Leg Ulcers in Sickle Cell Disease: A Multifactorial Analysis Highlights the Hemolytic Profile

Sickle cell disease (SCD) is characterized by the presence of the variant S hemoglobin (HbS). The homozygous genotype (HbSS) is sickle cell anemia (SCA), while the double heterozygous of HbS and HbC (HbSC) is defined as SC hemoglobinopathy. The pathophysiology is based on chronic hemolysis, inflammation, endothelial dysfunction, and vaso-occlusion, which results in vasculopathy and serious clinical manifestations. Sickle leg ulcers (SLUs) are cutaneous lesions around the malleoli frequent in 20% of Brazilian patients with SCD. SLUs present a variable clinical and laboratory pattern modulated by several characteristics that are not fully understood. Hence, this study aimed to investigate laboratory biomarkers and genetic and clinical parameters associated with the development of SLUs. This descriptive cross-sectional study included 69 SCD patients, 52 without SLU (SLU−) and 17 with active or previous SLU history (SLU+). The results showed a higher incidence of SLU in SCA patients and there was no observed association of α-3.7 Kb thalassemia in SLU occurrence. Alterations in NO metabolism and hemolysis were associated with clinical evolution and severity of SLU, in addition to hemolysis modulating the etiology and recurrence of SLU. Our multifactorial analyses demonstrate and extend the role of hemolysis driving the pathophysiological mechanism of SLU.

SLUs are cutaneous lesions that frequently affect the malleoli in lower extremities [8][9][10]. Usually, SLUs are superficial lesions with elevated edges and may present bloody, serous, or purulent exudate [11]. The SLU wound bed may present unviable tissues, such as necrotic tissue, owing to the accumulation of dead cells or sloughy tissue, which is characterized by cell fragments and absence of vascularization. Furthermore, the SLU wound bed may also have viable tissues, such as granulation tissue, which corresponds to angiogenesis, as well as epithelized tissue, consisting of regenerated and dry epidermis [8,11]. In addition, the size of the SLU, the period of time in which the SLU remained open, and the SLU recurrence are important characteristics whose influencing factors are not fully understood [12].
In this sense, intravascular hemolysis, sterile inflammation, reduced nitric oxide (NO) bioavailability, and endothelial dysfunction have been associated with SCD pathophysiology [13]. However, this association is not fully explained in SLU occurrence nor is its role in variable clinical evolution of SLU.
Genetic parameters are usually insufficiently explored in studies involving SLUs. Genetic modifiers, such as alpha deletion of 3.7 kb thalassemia (α-3.7 Kb thalassemia), may be useful in elucidating the pathophysiology in SLUs [14]. Likewise, individuals with SCD who carry α-3.7 Kb thalassemia may present laboratory alterations related to increased blood viscosity, such as a higher red blood cell (RBC) count, hemoglobin (Hb), and hematocrit (Hct) concentration, in addition to lower mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) [15].
Hence, considering the association between hemolysis and SLU, and the importance of understanding the multifactorial mechanism associated with SLU development, the present study aimed to characterize the SLU. We investigated laboratory biomarkers, genetics, and clinical parameters associated with SLUs.

Study Design
The present descriptive cross-sectional study included 69 SCD patients, 42% (29/69) with SCA and 58% (40/69) with HbSC disease, all seen at the Itabuna Sickle Cell Disease Reference Center (CERDOFI), in the state of Bahia, Brazil. Seventy-five percent (52/69) patients did not present SLU (SLU−) and 25% (17/69) presented active SLU or reported a previous history (SLU+). Regarding hydroxyurea (HU), 82.3% (14/17) of SLU+ patients and 53.8% (28/52) of SLU− patients were taking HU; owing to clinical severity, these patients could not stop using HU at the time of the study. All patients that were in steady state were included in the study, and this condition was defined as an absence of painful vaso-occlusive crises and absence of blood transfusion for 3-4 months. Patients without SCD (HbSS and HbSC) were excluded from the study. This work was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of the Santa Cruz State University (UESC) (protocol number: 11765319.7.0000.5526). Informed consent was obtained from all subjects involved in the study.

Clinical Data
The clinical data were collected using a standardized and confidential questionnaire self-reported at the time of the study enrollment and later confirmed by the medical records at CERDOFI. The clinical manifestations presented by the patients in the last six months of the day of the blood collection were investigated. Among SLU+ patients, 76.5% (13/17) had active SLU and 23.5% (4/17) had healed SLU at study enrollment. The clinical descriptions of active SLUs were performed by the medical and nursing staff of CERDOFI and recorded in the medical record.

Laboratory Determinations
Laboratory analyses were performed at Genetics and Applied Pathology Laboratory (LAPAGEN), UESC, as well as at Clinical Analyses Laboratory (LACTFAR), College of Pharmaceutical Sciences, Federal University of Bahia (UFBA). The nitric oxide metabolites (NOm) and genetics analyses were conducted at the Laboratory of Investigation in Genetics and Translational Hematology (LIGHT), Gonçalo Moniz Institute (IGM), Oswaldo Cruz Foundation (FIOCRUZ), Bahia, Brazil.
Hematological analyses were performed using an automatic hematology analyzer ABX Pentra 80 (HORIBA Medical, Montpellier, France). Reticulocytes were counted after staining supravitally with brilliant cresyl blue dye. Hemoglobin profiling and determination of HbF levels were assessed by high-performance liquid chromatography using an HPLC/Variant II hemoglobin testing system (Bio-Rad, Hercules, CA, USA).
The NOm were determined in serum samples using Griess reagent, according to the method previously described [16].
To perform genetics analyses, leukocyte genomic DNA was extracted employing the QIAamp extraction kit (Qiagen, Hilden, Germany). Allele-specific PCR was used to detect the α-3.7 Kb thalassemia deletion, according to the method previously described [17].

Statistical Analyses
Statistical analyses were conducted using the software program Statistical Package for the Social Sciences (SPSS) version 22.0 (IBM Software, New York, NY, USA). GraphPad Prism version 6.0 (Graphpad Software, La Jolla, CA, USA) was used for graph assembly. Shapiro-Wilk test was used to determine quantitative variables' distribution. The Mann-Whitney U test and independent t-test were used to compare the groups according to the normality of the distribution for each variable. Linear regression multivariate (LRM) analysis was performed to evaluate possible associations between the recurrence of SLUs and laboratory biomarkers with regard to the outcome of interest, SLU. The principal component analysis (PCA) is a common method employed for the identification of predictor factors in medical sciences [18]. A 15 × 9 matrix was assembled and data were previously auto-scaled in order to diminish the differences between the magnitudes. PCAs were performed using Statistica 10.0 software (StatSoft Inc., Tulsa, OK, USA). p values < 0.05 were considered statistically significant.

Clinical Characterization of SLUs
The results showed that 41.2% SLU+ patients experienced the first SLU during pediatric age (13-17 years), while 35.2% experienced it during adulthood (18-30 years) ( Table 1). The leading cause of SLU onset was trauma in the lower extremities (Table 1).
Additionally, 64.7% SLU+ patients presented SLU in the left or right malleolus, while 23.5% presented SLU on both malleoli simultaneously (Table 1). Further, 17.6% SLU+ patients developed SLUs that were open for 3 months and 82.4% for 4 months or years (Table 1). Moreover, 82.4% SLU+ patients presented up to three SLU recurrences, along with 17.6% who presented four to seven SLU recurrences (Table 1).

Laboratory Parameters in SLU− and SLU+ Patients
The results showed that SLU+ patients had lower RBC, segmented neutrophils and absolute reticulocyte counts, and Hb and Hct levels, as well as higher HbS, HbF, MCV, MCH, and platelet counts (p < 0.05) ( Table 2). In addition, SLU+ patients had higher LDH, total and indirect bilirubin, AST, GGT, uric acid, and iron levels (p < 0.05) ( Table 3).

Genetic Parameters in SLU− and SLU+ Patients
Among SCA and HbSC patients, 76.5% of SLU+ patients were SCA and 23.5% were HbSC (p < 0.05). Among SCA patients, the mean age of the first SLU was 20.9 ± 8.4 years, whereas in HbSC patients, the mean age was 34.0 ± 14.0 years (p < 0.05).
Additionally, laboratory biomarkers were associated with α-3.7 Kb thalassemia among SLU− and SLU+ patients. Regarding patients without α-3.7 Kb thalassemia, SLU+ patients had a lower RBC count and Hb and Hct concentration, in addition to higher MCV, MCH, LDH, total and indirect bilirubin, AST, GGT, and iron levels (p < 0.05) (Table S1). Among patients with α-3.7 Kb thalassemia, SLU+ patients had a lower RBC count, Hb, Hct, and MCHC concentration, in addition to higher MCV, MCH, LDH, total and indirect bilirubin, AST, and iron levels (p < 0.05) (Table S1).

Hemolytic Index in SLU Occurrence
PCA was performed to identify predictive factors for SLU+ patients. The results showed two principal components (PCs) with 82.8% of total variance (Figure 1).
The two PCs were hemolytic biomarkers that are strongly correlated with SLU occurrence, as the coefficients were higher than 0.5 (Table 4).
Correlation analyses between PCs and different variables demonstrated that PC1 was responsible for 45.75% of the total variance, including RBC and reticulocyte counts, as well as Hct and Hb levels. PC2 was responsible for 37.07% of total variance, including LDH, AST, total and indirect bilirubin, and ferritin levels ( Figure 2).

Hemolytic Biomarkers and HbF Levels in SLU Recurrence
A linear regression multivariate (LRM) model was performed with SLU recurrence as the dependent variable. Our model shows that Hb, Hct, LDH, indirect bilirubin, ferritin, and HbF levels were independently associated with SLU recurrence (Table 5). The two PCs were hemolytic biomarkers that are strongly correlated with SLU occurrence, as the coefficients were higher than 0.5 (Table 4). Correlation analyses between PCs and different variables demonstrated that PC1 was responsible for 45.75% of the total variance, including RBC and reticulocyte counts, as well as Hct and Hb levels. PC2 was responsible for 37.07% of total variance, including LDH, AST, total and indirect bilirubin, and ferritin levels ( Figure 2).

Hemolytic Biomarkers and HbF Levels in SLU Recurrence
A linear regression multivariate (LRM) model was performed with SLU recurrence as the dependent variable. Our model shows that Hb, Hct, LDH, indirect bilirubin, ferritin, and HbF levels were independently associated with SLU recurrence (Table 5). Table 5. Linear regression multivariate model of SLU recurrence in aassociation with laboratory biomarkers.
Serous and purulent exudates were associated with increased white blood cells (WBC) ( Figure 3G) and monocyte ( Figure 3H) and lymphocyte (p < 0.05) counts, as well as HbS, ferritin, and uric acid levels (p < 0.05). Sick edges were associated with increased SLU+ patients with recalcitrant SLU (>6 months) presented decreased RBC counts ( Figure 3C) and Hb levels, as well as increased NOm ( Figure 3D), HbS, and HbF levels (p < 0.05). SLU+ patients who had more than one SLU also presented lower Hb ( Figure 3E) and Hct, as well as higher NOm ( Figure 3F), AST, and ferritin levels (p < 0.05).

Discussion
The underlying mechanism responsible for SLUs is thought to be multifactorial. In our study group, the first SLU occurred after 12 years of age, which is in agreement with previous studies [13,19,20]. Most of the SLU+ patients presented lesions in the lateral or medial malleolus, and a few patients had lesions in both malleoli. Malleolar involvement may be justified by thin skin, a low amount of local subcutaneous fat, in addition to the expressive susceptibility of the marginal microcirculation to be obstructed by sickled RBCs, generating low blood flow and intravascular erythrocyte destruction [9,21].
Trauma in the malleolus has been suggested as the primary physical risk factor for SLU opening [8,19]. We observed that most SLU+ patients experienced traumatic episodes in malleoli, such as scratches, insect bites, and domestic accidents, prior to SLU opening [19,22].
Investigation of laboratory parameters showed higher levels of HbS, LDH, AST, and total and indirect bilirubin in SLU+ patients. These results reinforce the previous notion that SLUs are associated with SCD hemolytic subphenotype [19,23,24]. In addition, reduced RBC count and decreased Hb and Hct concentration in SLU+ patients correspond to anemia. This hemolysis promotes endothelial dysfunction and vasculopathy, while local inflammation, characterized by intense production of pro-inflammatory cytokines and leukocytes, such as neutrophils and monocytes, enhances the ongoing pathophysiology [13,25,26]. The PCA demonstrated two hemolytic components associated with SLUs. Thus, this paper corroborates previous studies that demonstrate the association between hemolysis markers with different clinical manifestations in SCD [27,28].
Additionally, SLUs were more frequent in SCA patients compared with HbSC; likewise, SLUs occurred earlier in SCA patients than in HbSC patients. Therefore, individuals who carry the HbSS genotype, the most severe genotype of SCD, may be at a greater risk of developing SLUs [13]. Regarding α-3.7 Kb thalassemia, there was a low frequency in SLU+ patients; however, the hemolytic profile in the SCD was not influenced by the deletion [29]. Interestingly, SLU+ patients showed a 23.5% increase in uric acid levels in comparison with SLU− patients. Previous studies suggest that increased uric acid levels may indicate erythrocyte hyperplasia in the bone marrow in response to hemolysis [25]. It may also indicate increased oxidative stress, resulting in reduced NO bioavailability [25,30]. These findings reinforce the association of high uric acid levels with hemolysis in SLU occurrence.
Hemoglobin metabolism in SCD is characterized by elevated indirect bilirubin levels and subsequent production of gallstones, which could cause cholelithiasis and increased GGT levels, as a hemolysis consequence [31]. In this study, SLU+ patients presented higher GGT levels. Ballas (1991) observed that SCD patients presented SLU and cholelithiasis simultaneously, although no association was found [32]. In our study, none of the SLU+ patients reported a diagnosis of cholelithiasis. However, high levels of GGT and indirect bilirubin reinforce the chronic hemolysis associated with SLU occurrence and predisposition to cholelithiasis.
Previous evidence about HbF in SLUs is controversial as there is no consensus about a protective role [12,19,33]. This study found higher levels of HbF in SLU+ patients, while an LRM model demonstrated that HbF levels were independently associated with SLU recurrence (R 2 = 0.981; p < 0.05). Despite these observations, this study was unable to determine the influence of HbF in SLUs because 60.8% (42/69) of SCD patients were taking HU. HU is the main pharmacological therapy for SCD, known for increasing HbF concentrations [25].
Regarding SLU recurrence, a study proposed that frequent hemolysis added to microvascular injury may be the main risk factor for inefficient healing and SLU reopening [8]. The LRM model from this study found that hemolytic biomarkers were independently associated with SLU recurrence for up to seven episodes (R 2 = 0.981; p < 0.05). Therefore, the results suggest that chronic hemolysis is associated with the predisposition to SLU recurrence and its variability.
Laboratory biomarkers were also associated with clinical aspects of SLUs. We found hemolytic biomarkers in association with necrotic and sloughy tissues in SLUs, which is in agreement with hemolytic anemia. Previous analysis indicates that hemolysis and anemia are predictive factors that may result in unsuccessful treatment of SLUs [12]. SLUs remained open from weeks to years among SLU+ patients, which demonstrates the variability in healing time. SLU+ patients with recalcitrant SLUs (>6 months) had severe anemia. Additionally, patients with more than one SLU simultaneously had altered hemolytic biomarkers levels. Therefore, SLUs with unviable tissues, recalcitration, and multiple SLU occurrence might be modulated by hemolysis that favors vasculopathy and delays healing. Furthermore, SLUs present predominantly purulent exudates and association with inflammatory cells, suggesting active inflammation and increased susceptibility to local clinical severity.
Additionally, NOm levels were associated with recalcitrant SLUs, simultaneous SLU occurrence, and sick edges in SLUs, which suggests that alterations in NO metabolism lead the severity of clinical characteristics in SLUs.

Conclusions
In summary, the results of this study corroborate the SLU pathophysiology as multifactorial because laboratory biomarkers and genetic and clinical parameters are responsible for modulating the SLU etiology, clinical evolution, and recurrence. The descriptive systematization of data associating laboratory biomarkers related to hemolysis with clinical aspects of SLUs has been rarely performed. Thus, we believe our results promote the understanding of both local and systemic alterations that may be useful to improve clinical practice.
Supplementary Materials: The following supporting information can be downloaded at https:// www.mdpi.com/article/10.3390/hematolrep15010013/s1, Table S1: Laboratory parameters of SLU− and SLU+ patients according to α-3.7 Kb thalassemia.  Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: Data are owned and saved by the affiliated CERDOFI and are available upon request to the corresponding author. For researchers meeting the criteria for access to confidential data, please contact the following email address: mmaleluia@uesc.br.